Governments are looking more and more to invest in renewable energy sources due to the energy transition that is currently taking place. One of the many renewable energy sources is wind energy which is increasingly positioned at sea. Wind turbines in deep parts of the ocean can be placed on floating structures which are often moored to the sea bottom by mooring ropes. For deep sea, the only viable option is a synthetic mooring line due to its almost neutral buoyancy.
Mooring ropes have a vital role in the offshore floating structure as it is keeping the structure in place. When a mooring line breaks, the consequences may be big, leading to serious damage or dangerous situations. Therefore, the structural integrity of mooring ropes should be evaluated regularly. For synthetic mooring ropes, the only method at this point in time is visual inspection. This can be done by divers or by Remotely Operated Vehicles (ROVs). This method is expensive, time consuming and in case it is done by divers, it is potentially dangerous. Furthermore, synthetic mooring ropes are susceptible to external damage which means inspection would have to be executed without direct contact with the mooring ropes. Therefore, it is necessary to assess the feasibility of a non-contact, non-destructive testing method in order to assess the structural integrity of a synthetic mooring line. The combination of non-destructive material property assessment and tension assessment is believed to produce a structural health monitoring instrument for synthetic mooring ropes.
In this thesis, a methodology is proposed which uses two independent non-contact, non-destructive measurements to assess the structural integrity of a high modulus polyethylene (HMPE) rope specimen. The measurements involved are ultrasonic guided wave (UGW) measurements and vibration measurements. The UGW measurements are performed to assess the stiffness of the test specimen according to the principle of attenuation of ultrasonic waves propagating through a specimen. The vibration measurements are performed to assess the natural frequencies of a manually excited test specimen. The assessed natural frequencies and the determined stiffness of the test specimen can be used to calculate the load acting on the test specimen.
The methodology is tested by conducting experiments in a laboratory environment where in-situ conditions are recreated by performing the tests underwater. It was concluded that the loads can be recalculated with varying accuracy of approximately 10% with respect to the actual values, with increasing accuracy for higher load values. It is concluded that the proposed methodology has the potential to determine load on a synthetic mooring line in a non-contact, non-destructive manner.

Floating Offshore Wind Turbines (FOWTs) have emerged as a promising technology for generating clean energy in deep water locations. Bluewater Energy Services proposes a Tension Leg Platform (TLP) as the floating support structure. An effective Structural Health Monitoring (SHM) system (of which there are various types) can facilitate timely interventions and optimize inspection and maintenance activities by providing continuous insights into their structural condition. Fatigue damage is especially critical for the support structures of FOWTs, as they are subject to cyclic loads that can cause structural damage.

This research proposes a fatigue monitoring system for a TLP supporting FOWTs. The methodology used is Modal Decomposition and Expansion (MDE). Due to the complexity of the studied structure in terms of structural dynamics, MDE is selected for its ability to capture dynamic behaviour. The main objective of the fatigue monitoring system is to perform the full-field strain estimation based on a limited number of sensors. This could also allow for the verification of the design considerations. With the presented response reconstruction approach, the stress in the locations prone to fatigue of the platform can be monitored and therefore, enabling estimation of the remaining lifetime of the structure and optimize maintenance planning.

Different analytical and numerical models are used in this investigation. The application of MDE in a simple structure (i.e. a cantilever beam) is first assessed to verify the performance and to gain insights of the methodology. Later, MDE is applied to a simplified TLP model to validate the response reconstruction approach and demonstrate its applicability for TLP-like structures.

Finally, a FOWT numerical model is used to design the fatigue monitoring system. The proposed system consists of two layouts of two strain gauges in the upper column of the TLP, and two layouts of two strain gauges on each pontoon. This system can provide full-field strain estimations with over 88.9% accuracy and predict fatigue damage accumulation with errors of less than 0.01%. Also, the system presented in this thesis only predicts global responses. However, the fatigue of the structure is also influenced by local structural responses due to sea pressures. Therefore, future research to include local effects in the predictions is recommended.

Floating offshore production units are typically anchored to the seabed with mooring chains. Structural degradation of mooring chain steel can lead to premature failure with large environmental and financial consequences. In the oceanic environment, corrosion and fatigue are the dominant failure modes for mooring chains. These damage mechanisms are hard to predict and even harder to identify at early stages of damage evolution. Continuous research to develop improved monitoring techniques is performed to increase the safety and reliability of these structures. However, inspection techniques that can accurately and quantitatively diagnose these damage mechanisms in the submerged steel parts are yet insufficient.

Acoustic emission (AE) monitoring is a non-destructive evaluation technique that can identify structural degradation in solid materials. The technique consists of recording and processing the ultrasonic waves generated by irreversible changes in the material matrix due to damage growth. This research is focused on the global parametric analysis of the primary features of AE signals recorded during corrosion-fatigue experiments performed with submerged steel and non-contact sensors. Three experiments have been analysed to assess which of the AE primary features can most accurately correlate to the fatigue damage evolution.

Signal characterization based on their energy and duration was performed to distinguish three levels of severity. Based on a global parametric analysis the hit-rate and energy-rate have the highest potential and show good correlation to the corrosion-fatigue damage evolution. However, the global features seem to differ notably between different samples and several moments with absence of recorded activity precede final failure. Performing assessment only based on the global features is not considered sufficient. Thus, local analysis methods for AE signals is suggested to extract further information on the source of the emitting damage mechanisms.